Last week I was part of a business roundtable for Congressman Kevin Cramer. There were several topics discussed but I presented some information about the labor force in the North Dakota metropolitan and micropolitan areas. I calculated three-year and one year monthly growth rates and then projected out the labor force based on those rates. This is an inherently linear projection method which is less than desirable but the inherent nonlinearities in the ND data are somewhat difficult to identify.
Using the monthly growth rate in labor force over the last year gives the following picture:
That light blue line, assuming you have a color screen, is the Williston labor force. The red line is the Grand Forks labor force. Maybe the first area of concern is the negative slope for the Grand Forks labor force. That’s,…not good. Labor force is the sum of employed and unemployed, so if this number is declining it is a sign of potential labor constraint in the community, which unfortunately fits with many, if not most, of the stories I hear about Grand Forks right now. In this scenario we see Williston pass Grand Forks in early 2018. The non-metropolitan and micropolitan areas (by current definitions), essentially the rural counties, will pass Grand Forks in labor force in early 2015.
When we use the monthly growth rate in labor force based on data from the last three years the picture changes a bit:
First off, nothing major changes with the timing of the rural areas passing Grand Forks (it really does not have the ability to change in a major way). However there is a big change when it comes to Williston. Williston will pass Grand Forks in mid-2016, almost two full years earlier than the other graph indicates. Another major change is that Williston passes Bismarck in this projection.
Now the right question to ask here is how likely is all this to happen? That is not entirely clear. I am actually working with a student to understand the impact of the oil boom on demographic rates that will allow us to arrive at better estimates and actual predictions about where the population and other variables are heading. This should aid in planning for businesses and government alike.